Multiple Criteria Decision Analysis under uncertainty in sustainable construction: a neutrosophic modified best-worst method

SUSTAINABLE BUILT ENVIRONMENT D-A-CH CONFERENCE 2019

生态环境科学

Scherz, M.^1 ; Vafadarnikjoo, A.^2

Working Group Sustainable Construction, Institute of Technology and Testing of Construction Materials, Graz University of Technology, Austria^1

Norwich Business School, University of East Anglia, Norwich, United Kingdom^2

关键词: Analytic hierarchy process (ahp);    Construction process;    Multiple criteria decision analysis;    Pair-wise comparison;    Subjective judgement;    Sustainable construction;    Uncertainty handling;    Weights of evaluation criterion;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/323/1/012098/pdf
DOI  :  10.1088/1755-1315/323/1/012098

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Capturing uncertainty in multiple criteria decision analysis (MCDA) is not a new theme but a largely developing topic which is in close connection with uncertainty theories such as fuzzy set and grey systems theories. Due to growing complexity of construction processes mainly because of implementation of sustainability aspects it would be necessary to take advantage of a novel MCDA methodology as an efficient tool to handle the uncertainty in sustainable construction decision making. In this study, we utilise a novel neutrosophic modified best-worst method (NM-BWM) to deal with the uncertainty in decision making in the context of sustainable construction. The method is an integration of neutrosophic set theory (NST) and the modified best-worst method (M-BWM). The NST can provide insights on efficient uncertainty handling of decision makers (DMs) subjective judgements. The BWM is a MCDA method which utilises two vectors of pairwise comparisons (the best criterion to others and others to the worst criterion) to obtain the weights of evaluation criteria. Merits of the BWM include its capability in effectively remedying the inconsistency derived from pairwise comparisons as well as simplicity and less pairwise comparisons compared to other similar methods like analytic hierarchy process (AHP). We show the applicability of the method in a case study with focus on the implementation of sustainable construction.